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Why a global federation might be needed to manage AI

Rufo Guerreschi.
https://www.linkedin.com/in/rufoguerreschi.

Coalition for a Baruch Plan for AI
https://www.cbpai.org/

0:00 Intro.
0:21 Rufo Guerreschi.
0:28 Contents.
0:41 Part 1: Why we have a governance problem.
1:18 From e-democracy to cybersecurity.
2:42 Snowden showed that international standards were needed.
3:55 Taking the needs of intelligence agencies into account.
4:24 ChatGPT was a wake up moment for privacy.
5:08 Living in Geneva to interface with states.
5:57 Decision making is high up in government.
6:26 Coalition for a Baruch plan for AI
7:12 Parallels to organizations to manage nuclear safety.
8:11 Hidden coordination between intelligence agencies.
8:57 Intergovernmental treaties are not tight.
10:19 The original Baruch plan in 1946
11:28 Why the original Baruch plan did not succeed.
12:27 We almost had a different international structure.
12:54 A global monopoly on violence.
14:04 Could expand to other weapons.
14:39 AI is a second opportunity for global governance.
15:19 After Soviet tests, there was no secret to keep.
16:22 Proliferation risk of AI tech is much greater?
17:44 Scale and timeline of AI risk.
19:04 Capabilities of security agencies.
20:02 Internal capabilities of leading AI labs.
20:58 Governments care about impactful technologies.
22:06 Government compute, risk, other capabilities.
23:05 Are domestic labs outside their jurisdiction?
23:41 What are the timelines where change is required?
24:54 Scientists, Musk, Amodei.
26:24 Recursive self improvement and loss of control.
27:22 A grand gamble, the rosy perspective of CEOs.
28:20 CEOs can’t really say anything else.
28:59 Altman, Trump, Softbank pursuing superintelligence.
30:01 Superintelligence is clearly defined by Nick Bostrom.
30:52 Explain to people what “superintelligence” means.
31:32 Jobs created by Stargate project?
32:14 Will centralize power.
33:33 Sharing of the benefits needs to be ensured.
34:26 We are running out of time.
35:27 Conditional treaty idea.
36:34 Part 2: We can do this without a global dictatorship.
36:44 Dictatorship concerns are very reasonable.
37:19 Global power is already highly concentrated.
38:13 We are already in a surveillance world.
39:18 Affects influential people especially.
40:13 Surveillance is largely unaccountable.
41:35 Why did this machinery of surveillance evolve?
42:34 Shadow activities.
43:37 Choice of safety vs liberty (privacy)
44:26 How can this dichotomy be rephrased?
45:23 Revisit supply chains and lawful access.
46:37 Why the government broke all security at all levels.
47:17 The encryption wars and export controls.
48:16 Front door mechanism replaced by back door.
49:21 The world we could live in.
50:03 What would responding to requests look like?
50:50 Apple may be leaving “bug doors” intentionally.
52:23 Apple under same constraints as government.
52:51 There are backdoors everywhere.
53:45 China and the US need to both trust AI tech.
55:10 Technical debt of past unsolved problems.
55:53 Actually a governance debt (social-technical)
56:38 Provably safe or guaranteed safe AI
57:19 Requirement: Governance plus lawful access.
58:46 Tor, Signal, etc are often wishful thinking.
59:26 Can restructure incentives.
59:51 Restrict proliferation without dragnet?
1:00:36 Physical plus focused surveillance.
1:02:21 Dragnet surveillance since the telegraph.
1:03:07 We have to build a digital dog.
1:04:14 The dream of cyber libertarians.
1:04:54 Is the government out to get you?
1:05:55 Targeted surveillance is more important.
1:06:57 A proper warrant process leveraging citizens.
1:08:43 Just like procedures for elections.
1:09:41 Use democratic system during chip fabrication.
1:10:49 How democracy can help with technical challenges.
1:11:31 Current world: anarchy between countries.
1:12:25 Only those with the most guns and money rule.
1:13:19 Everyone needing to spend a lot on military.
1:14:04 AI also engages states in a race.
1:15:16 Anarchy is not a given: US example.
1:16:05 The forming of the United States.
1:17:24 This federacy model could apply to AI
1:18:03 Same idea was even proposed by Sam Altman.
1:18:54 How can we maximize the chances of success?
1:19:46 Part 3: How to actually form international treaties.
1:20:09 Calling for a world government scares people.
1:21:17 Genuine risk of global dictatorship.
1:21:45 We need a world /federal/ democratic government.
1:23:02 Why people are not outspoken.
1:24:12 Isn’t it hard to get everyone on one page?
1:25:20 Moving from anarchy to a social contract.
1:26:11 Many states have very little sovereignty.
1:26:53 Different religions didn’t prevent common ground.
1:28:16 China and US political systems similar.
1:30:14 Coming together, values could be better.
1:31:47 Critical mass of states.
1:32:19 The Philadelphia convention example.
1:32:44 Start with say seven states.
1:33:48 Date of the US constitutional convention.
1:34:42 US and China both invited but only together.
1:35:43 Funding will make a big difference.
1:38:36 Lobbying to US and China.
1:38:49 Conclusion.
1:39:33 Outro

Meta AI Could Get Its Own Standalone App Like ChatGPT, Grok, Perplexity, And Gemini

Meta AI will soon become one of the social media company’s standalone apps, joining Facebook, Instagram and WhatsApp, CNBC has learned.

S plans to make his company the leader in artificial intelligence by the end of the year, ahead of competitors such as OpenAI and Alphabet, said the people, who asked not to be named because the project is confidential. + The Meta AI chatbot launched in September 2023, with the company pitching it as a generative AI-powered digital assistant that can provide responses and create images based on user prompts within its existing apps. The company brought Meta AI to the forefront of its apps in April, when it replaced the search feature for Facebook, Instagram, WhatsApp and Messenger with the chatbot.

S generative AI technologies to billions of consumers. This is going to be the year when a highly intelligent and personalized AI assistant reaches more than 1 billion people, and I expect Meta AI to be that leading AI assistant, Zuckerberg told analysts during the company s apps such as Facebook and WhatsApp. Although Meta [ https://open.substack.com/pub/remunerationlabs/p/meta-ai-cou…Share=true](https://open.substack.com/pub/remunerationlabs/p/meta-ai-cou…Share=true)


The Meta AI app marks a major step in CEO Mark Zuckerberg’s plan to make his company the leader in AI by the end of the year, ahead of competitors such as OpenAI and Alphabet, the people said.

Japanese Scientist Develops ‘Living’ Skin For Robots! #shorts

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Is This the Future? Japanese Scientists Create Living Robots with Human Skin! Joe Rogan Experience

Discover the groundbreaking advancements in robotics as Annie Jacobsen and Joe Rogan discuss a startling innovation: a robot made from living human skin. This fascinating creation not only smiles but raises ethical questions about the future of artificial humans. How close are we to creating a fully artificial person? Join the conversation about the implications of these technologies, especially in countries with different regulations. Don’t miss this eye-opening discussion!

Living robot skin

In a scientific breakthrough, Japanese scientists have found a way to attach artificially created living skin to robot faces for more realistic smiles and facial expressions.

#japan #robots #wion.

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LIVE NOW! Blue Ghost’s Historic Moon Landing: Science, Innovation & The Future of Space

Firefly Aerospace’s Blue Ghost lunar lander is set to make history as it targets a March 2 lunar landing near Mare Crisium, a vast plain on the Moon’s near side. Carrying NASA’s cutting-edge science and technology, this mission marks another crucial step in humanity’s return to the Moon under the Artemis program. As part of NASA’s CLPS initiative, Blue Ghost’s success will pave the way for future lunar and Martian exploration.

Mission Overview: Blue Ghost’s Lunar Delivery.
Launched aboard a SpaceX Falcon 9 on January 15, Blue Ghost carries 10 NASA payloads designed to investigate the Moon’s environment and test new technologies for future missions. These experiments will provide critical data on lunar surface conditions, radiation levels, thermal properties, and advanced landing systems—all essential for upcoming crewed missions.

Live Landing Coverage & Key Moments.
The landing event, hosted by NASA and Firefly Aerospace, will be streamed live on NASA+ and Firefly’s YouTube channel starting at 2:20 a.m. EST on March 2, roughly 75 minutes before touchdown. The stream will cover the final descent, landing confirmation, and initial mission updates. A post-landing press conference will follow, where experts will discuss the mission’s success and upcoming science operations on the lunar surface.

Why This Mission Matters.
Blue Ghost is a key part of NASA’s Commercial Lunar Payload Services (CLPS) program, which enables private companies to deliver science and technology to the Moon. These robotic landings will support Artemis astronauts, testing vital systems for future long-term lunar habitation and, ultimately, crewed missions to Mars. NASA’s collaboration with companies like Firefly Aerospace ensures rapid progress in space exploration, resource utilization, and sustainable lunar development.

The Future of Lunar Exploration.
With CLPS contracts valued at $2.6 billion through 2028, NASA is committed to building a strong commercial space ecosystem. The $101.5 million contract awarded to Firefly for this mission underscores the agency’s dedication to fostering innovative, cost-effective lunar transportation solutions. Future missions will refine navigation, in-situ resource utilization, and long-duration surface operations, bringing us closer to a permanent human presence beyond Earth.

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A-MEM: A Novel Agentic Memory System for LLM Agents that Enables Dynamic Memory Structuring without Relying on Static, Predetermined Memory Operations

Paper: https://arxiv.org/abs/2502.12110v1

GitHub Page: https://github.com/WujiangXu/AgenticMemory


Current memory systems for large language model (LLM) agents often struggle with rigidity and a lack of dynamic organization. Traditional approaches rely on fixed memory structures—predefined storage points and retrieval patterns that do not easily adapt to new or unexpected information. This rigidity can hinder an agent’s ability to effectively process complex tasks or learn from novel experiences, such as encountering a new mathematical solution. In many cases, the memory operates more as a static archive than as a living network of evolving knowledge. This limitation becomes particularly apparent during multi-step reasoning tasks or long-term interactions, where flexible adaptation is crucial for maintaining consistency and depth in understanding.

Researchers from Rutgers University, Ant Group, and Salesforce Research have introduced A-MEM, an agentic memory system designed to address these limitations. A-MEM is built on principles inspired by the Zettelkasten method—a system known for its effective note-taking and flexible organization. In A-MEM, each interaction is recorded as a detailed note that includes not only the content and timestamp, but also keywords, tags, and contextual descriptions generated by the LLM itself. Unlike traditional systems that impose a rigid schema, A-MEM allows these notes to be dynamically interconnected based on semantic relationships, enabling the memory to adapt and evolve as new information is processed.

At its core, A-MEM employs a series of technical innovations that enhance its flexibility. Each new interaction is transformed into an atomic note, enriched with multiple layers of information—keywords, tags, and context—that help capture the essence of the experience. These notes are then converted into dense vector representations using a text encoder, which enables the system to compare new entries with existing memories based on semantic similarity. When a new note is added, the system retrieves similar historical memories and autonomously establishes links between them. This process, which relies on the LLM’s ability to recognize subtle patterns and shared attributes, goes beyond simple matching to create a more nuanced network of related information.

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